FinOps AI / ML Engineer Manager
Quick Summary
Minimum of 8 years of experience in cloud engineering, AI automation,
Minimum of 8 years of experience in cloud engineering, AI automation,
Accenture's Cloud Advisory practice is a market leader in helping global enterprises achieve measurable financial and operational value from their cloud investments. Our FinOps and Cloud Economics teams combine rigorous financial governance with automation, AI, and deep technical expertise to drive sustained savings and speed-to-value across AWS, Azure, and Google Cloud. We are a collaborative team of architects, engineers, financial analysts, and delivery experts who partner with world-class clients to transform how they manage, optimize, and govern cloud spend.
A skilled solution architect and delivery leader with 8–12 years in cloud engineering, AI automation, or platform architecture who has spent 3–5 years leading FinOps automation programs. You are energized by building agentic AI systems that drive real cost governance outcomes, and you thrive guiding squads to ship production-grade automations across multi-cloud environments.
Define reference architectures for agentic AI orchestration (multi-agent patterns, event-driven workflows) and MCP integration with AWS, Azure, GCP, and enterprise systems
Establish frameworks for cost governance controls (budget thresholds, tagging, anomaly detection) using OPA/Rego or Sentinel; design IaC guardrails and reusable modules
Lead squads to implement agentic workflows, IaC modules, and policy libraries; ensure CI/CD integration and automated compliance checks
Mentor associate managers, consultants, and analysts on automation best practices and FinOps engineering standards
Operationalize Responsible AI standards (Policy 1010, Standard #7); ensure RBAC, secrets management, and auditability in all agentic workflows
Define KPIs for automation coverage, policy adherence, and realized savings; publish dashboards and executive readouts
Support proposals, client workshops, and SOW development for agentic-enabled FinOps programs
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
Requirements
~1 min read- Minimum of 8 years of experience in cloud engineering, AI automation, or platform architecture
- Minimum of 3 years leading FinOps automation programs
- Minimum 1 year experience in agentic AI frameworks (LangGraph, AutoGen, Crew-style patterns) and MCP integration
- Bachelor's degree in Computer Science, Engineering, IT, Data (or similar field) or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
Nice to Have
~1 min read- You hold a FinOps Certified Practitioner (FOCP) credential or CSP cloud certifications
- You have proficiency in Python/TypeScript; IaC (Terraform/Bicep/ARM); policy-as-code engines (OPA/Rego, Sentinel); CI/CD tools (GitHub Actions, Azure DevOps)
- You have additional certifications in Responsible AI or Cloud Architecture
- You have team lead or mentoring experience in a consulting or engineering organization
- Master's degree in Computer Science, Engineering, IT, Data (or similar field)
What We Offer
~4 min readVisit us at www.accenture.com
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Location & Eligibility
About this job
- Pay per year
- $94,400–$293,800 a year
- 8% below the $210,000 median for Machine Learning Engineer jobs on Jobera (948 salaries).
- Posted
- 3 days ago
Listing Details
- Posted
- October 30, 2026
- First seen
- November 1, 2026
- Last seen
- November 1, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- November 2, 2026
Signal breakdown
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